Remote HPC Reliability & AI Ops Engineer

EPAM Systems Inc; Chicago (IL); Remote; USD 155,000 - 175,000; Full time

Benefits offered by this job

Medical, Dental and Vision Insurance (

Health Savings Account

Flexible Spending Accounts (Healthcare

Short-Term and Long-Term Disability

Life and AD&D Insurance

Employee Assistance Program

LinkedIn learning access

Matched 401(k) Retirement Savings Plan

Paid Time Off

Job summary

EPAM Systems, Inc. is seeking an engineer with HPC and site-reliability experience to keep a multi-cloud AI infrastructure reliable and efficient.

You will investigate hard operational problems across compute, accelerators, workload scheduling, storage, and networking, turning findings into proactive detection and safe automated remediation, including AI-powered agents. Experience with production HPC, Linux, and telemetry correlation across clouds is required.

Qualifications

• Operations experience with production HPC, GPU/accelerator clusters, or large-scale distributed compute in a reliability-focused engineering role.
• Strong Linux and networking skills, debugging failures across processes, containers, storage I/O, DNS, connectivity, and authentication.
• Correlates telemetry across multiple cloud environments using tools such as Prometheus, Grafana, OpenTelemetry, or centralized logging, rather than relying on a single dashboard.
• Writes and maintains automation in a language such as Python or Go, and has owned complex production investigations from symptom through root cause to a verified, lasting fix

Responsibilities

• Build a working understanding of multi-cloud HPC architecture (clusters, schedulers, accelerators, storage, networking, authentication) and keep it current as the infrastructure changes
• Find reliability and performance problems proactively, correlating logs, metrics, and events across cloud providers to build a clear incident picture and spot gaps in telemetry
• Diagnose complex issues end to end across Linux hosts, containers, schedulers, distributed workloads, storage, networking, and accelerators, isolating root cause rather than treating symptoms
• Turn proven investigations into repeatable tooling and agent-enabled workflows for detection, diagnosis, and bounded remediation, with safety built in: scoped permissions, precondition checks, human approval where needed, rollback, and post-change verification
• Strengthen observability and monitoring, measure whether the automation actually works (accuracy, recovery time, recurrence, false positives), and partner with infrastructure, research, security, and cloud-provider teams to turn incident lessons into durable fixes

Skills

HPC operations

SRE

Python/Go

Prometheus

Grafana

OpenTelemetry

Linux

Containers

Kubernetes

Tools

Prometheus

Grafana

OpenTelemetry

Terraform

Kubernetes

Job description

EPAM Systems, Inc. is seeking an engineer with HPC and site-reliability experience to keep a multi-cloud AI infrastructure reliable and efficient.

You will investigate hard operational problems across compute, accelerators, workload scheduling, storage, and networking, turning findings into proactive detection and safe automated remediation, including AI-powered agents. Experience with production HPC, Linux, and telemetry correlation across clouds is required.